Unbiased Hiring: Tactical Tips to Help You Build Stronger, More Diverse Teams
August 15, 2018
Building a team that embraces diversity and inclusion can be challenging for any company, and some might say particularly challenging for tech companies. It is difficult to eliminate the hidden biases that exist in the traditional hiring process, but I recently had the chance to talk with someone who is a pioneer working to solve this exact problem.
Kate Glazebrook is the co-founder and CEO of Applied, a technology platform that uses behavioral and data science to remove bias from hiring decisions. In layman’s terms, it’s a hiring platform that helps you find the best person for the job, regardless of their background.
Kate started her career as an economist in the Australian government. While the connection between that job and her new role reshaping the way corporations hire talent may not be immediately apparent, there are some common threads. For instance, Kate’s work on pension and welfare policy focused on finding ways to ensure the promotion of social mobility in a way that didn’t systematically overlook huge swathes of the population just because they didn’t “look the part.”
In my conversation with Kate, we talked about why diversity matters (especially for tech companies), why these companies find addressing it challenging, and what Applied is doing to change hiring processes for the better. She also shared a few tips on what any company can do right now to initiate positive changes in how they hire.
How Diversity Makes Your Team Stronger
When someone asks Kate to explain why diverse teams are so important, she has the perfect answer. She asks,
“Can you give me a good reason why you wouldn’t want diversity in your team?”
Good question. There are, of course, a number of moral and ethical reasons why it’s important to build diversity into any team; but Kate points out that it’s not just about socio-demographic diversity, but also about socio-cognitive diversity.
There is a lot of research that supports the value of socio-cognitive diversity.
“The general consensus is that diverse teams tend to outperform homogenous teams, particularly when they’re working on projects that require creativity, innovation, or solving complex problems – situations in which not all the information about the problem is known.”
Sounds like every project I’ve worked on.
Part of the reason diverse teams have an edge is that people tend to work a little harder when they know that team members will be coming at the problem from different perspectives. They understand that they’ll need to bring their “A game” and present their perspective as persuasively as possible.
Diverse teams are less likely to degenerate into an innovation-killing echo chamber. “If you’re going into a conversation where you know what people think about the given topic, you can easily dodge things you don’t want to talk about and concentrate on areas of mutual interest,” Kate explains. Conversely, in a more diverse team, people go in prepared to develop and defend their ideas with more passion because they know their ideas will be judged against a wide range of solutions. As Kate points out,
“One of the easiest ways to accurately test your assumptions is to have somebody in the room who vehemently represents a slightly different perspective.”
Diversity is especially important for technology teams. Most technology companies want their products to have the widest appeal and application possible. Technology built by a diverse group is more likely to serve a diverse group and, ultimately, be more sustainable.
Common Roadblocks to Building a Diverse Team
So, if the benefits of diverse teams are so great, why aren’t more companies getting on board with building them? The short answer is that change is hard. People are used to doing things, like hiring, the way they’ve always been done. Also, hiring is a fairly complex process, so trying to unpack it and rework it feels like a huge undertaking.
When you start to break it down, however, Kate points out that there are really two main challenges: sourcing/attraction and selection. In other words, the problems most companies cite are:
- I can’t get a diverse group of people to apply for my job openings; and
- Even when I do have a diverse applicants, they aren’t getting hired.
With the Applied platform, Kate and her team are focused on helping teams overcome both of these problems, particularly around the selection stage of the process.
“We help make sure that when you have a diverse group of people, you’re not systematically overlooking certain applicants because the process you’re using inadvertently creates bias against them,” Kate says. “A lot of the challenge stems from the fact that most of us inherently feel most comfortable hiring people who look and feel a bit like us.”
In trying to maintain our comfort level, we are often overly reliant on tapping into our own networks to fill positions. In fact, many companies heavily incentivize employees to bring in candidates from their networks.
While this refer-a-friend approach may seem efficient on the surface (referred applicants are usually more likely to be accepted and integrate more easily into the team), the process is recursive. Any personal network is, by definition, a subset of the wider network. Focusing a candidate search within personal networks typically results in overlooking people based simply on how an individual’s relationships skew the pool.
Stereotypes are another problem. While hiring women into technology roles is one obvious area where this issue comes into play, it certainly isn’t the only one. Men, for instance, face similar prejudice when it comes to roles that deal with caring for young people. In any such case, the solution is the same. As Kate explains,
“You need to remove anything that distracts from the way you understand talent (like people’s names, where they went to school, and so forth) so you can really concentrate on the skills the candidate can bring to the role. That’s where you start to discover that diversity wins out.”
A New Hiring Methodology: Removing Bias
Knowing that they were just as likely to fall into the same hiring traps as other organizations, the team behind Applied ran a massive experiment in which they tested their new model of hiring against the traditional resume- or CV-based sifting process. They put real candidates through both processes simultaneously, allowing one team to review candidates based on their CVs and another team to review them based on their responses to skill-based questions that were part of the new de-biased methodology.
The new methodology involved a number of strategies and tactics, all geared toward removing bias by eliminating any information that would distract from the work of assessing a candidate’s actual skills. Four of the primary changes to the process were:
- Anonymizing the Applications: This involved removing names, education history and other details that might create bias in the reviewer.
- “Chunking” Applications by Area: By comparing candidates first on one aspect of the job and then the next aspect, the team was able to eliminate the “halo effect,” which biases judgement by transferring assessment of a person’s abilities in one area to bleed over into how we assess them in another area.
- Averaging Application Scores: The new methodology allowed multiple people to score applicants at the same time without seeing each other’s scores, and then all the separate scores were averaged together, allowing the team to leverage the wisdom of the crowd, so to speak.
- Randomizing Candidate Order: Finally, because there is some interesting research that time of day can have an impact on decisions, the team randomized when candidates appeared to reviewers.
After hacking a system that allowed them to focus on the things about a candidate that really mattered, the team discovered some interesting (if not totally unexpected) things:
- CV scores weren’t predictive in terms of how a candidate performed in later stages of recruitment. In fact, there was no correlation between CV performance and later stage performance. The skill-based scores, however, were very predictive of later performance.
- More than half the people hired would not have gotten the job under the traditional process. In fact, many of the people who ultimately made the cut would never have even made it to the interview stage under the CV-based process.
- Overall, the group of candidates selected for interviews were more diverse, meaning that the new methodology was not only more efficient at finding people who were more skilled, but also at diversifying the people the organization was hiring.
Things You Can Do Today
Even if you’re not ready to take advantage of a technology platform like Applied, there are still some steps Kate recommends to remove bias from your hiring process.
First, know that bias and diversity training don’t usually stick. While they can do a decent job of raising awareness, there’s not much correlation between the implementation of these kinds of courses and the candidate selection decisions made three weeks later based on reviewing CVs. Instead, you have to focus on how you structure the actual process.
Iris Bohnet, one of Applied’s advisors, wrote a book called, What Works: Gender Equality by Design. One of the main points she makes is how important it is to structure the hiring process properly. For instance, one of the traps companies often fall into is deciding what they care about after they’ve interviewed people. This approach of defining a role after seeing several candidates almost always leads to deciding what you care about based on the person you liked best.
A better approach is to define the skills you’re looking for before you start the process. Ideally, Kate recommends weighting each skill to give yourself a really clear benchmark against which to assess candidates. “This limits the usual ‘I liked them’ or ‘I didn’t like them’ kind of responses,” Kate explains. “Instead you can hone in on how good each candidate was in each of the skill areas you identified as important for the job.”
Applied uses this approach on a more sophisticated scale to help organizations implement a truly skills-focused hiring approach that naturally helps build team diversity. Their platform is a rare example of how technology can sometimes make us better humans, removing bias to ensure that the best people get the job.